潜艇使用自航式声诱饵防御鱼雷模型并行计算方法研究  被引量:7

Research on the parallel computing method of submarine’s torpedo defense model with self-propelled acoustic decoy

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作  者:李雯 迟利华[3] 张会 张哲[1,2] 刘杰 LI Wen;CHI Li-hua;ZHANG Hui;ZHANG Zhe;LIU Jie(Science and Technology on Parallel and Distributed Processing Laboratory,National University of Defense Technology,Changsha 410073;Laboratory of Software Engineering for Complex Systems,National University of Defense Technology,Changsha 410073;College of Computer Science and Electronic Engineering,Hunan University,Changsha 410082;Navy Submarine Academy,Qingdao 266199,China)

机构地区:[1]国防科技大学并行与分布处理重点实验室,湖南长沙410073 [2]国防科技大学复杂系统软件工程湖南省重点实验室,湖南长沙410073 [3]湖南大学信息科学与工程学院,湖南长沙410082 [4]海军潜艇学院,山东青岛266199

出  处:《计算机工程与科学》2020年第12期2163-2168,共6页Computer Engineering & Science

基  金:国家重点研发计划(2018YFB0204301,2017YFB0202104)。

摘  要:潜艇使用自航式声诱饵防御声自导鱼雷是水下防御的主要手段之一,传统穷举统计方法计算量随决策参数增多而急剧增加,无法满足实时性要求。从基于多实体有限状态机的鱼雷防御模型出发,提出了2级并行策略,在进程和线程间划分仿真循环,通过数据交换作出最优决策。实验结果表明,并行后的模型可以在短时间内作出和实际作战情况相近的决策,在404个方案仿真的计算量下,模型运行时间从144.65 s缩短至1.2 s,获得了120倍的加速比,有效解决了实时方案决策的问题。One of the main means of underwater defense is to use self-propelled acoustic decoy to defend the acoustic homing torpedo.The calculation amount of traditional exhaustive statistical method increases rapidly with the increase of decision parameters,which cannot satisfy the real-time requirements.According to the torpedo defense model based on a multi-entity finite state machine,this paper proposes a two-level parallel strategy,which divides the simulation cycle between processes and threads,and makes the optimal decision through data exchange.The experimental results demonstrate that the parallel model can make decisions identical to the actual combat situation in a short time.Under the calculation amount of 404 schemes simulation,the running time of the model is shortened from 144.65 s to 1.2 s,120 times faster than the original program,which effectively solves the dilemma of real-time scheme decisions.

关 键 词:自航式声诱饵 鱼雷防御 并行算法 

分 类 号:TP301[自动化与计算机技术—计算机系统结构]

 

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